The wireless systems that establish multiple input multiple output (MIMO) channels through multiple antennas at both ends of the communication link, have been proved to have tremendous potential to linearly lift the capacity of conventional scalar channel. In this paper, we present two efficient decision feedback equalization algorithms that achieve optimal and suboptimal detection order in MIMO spatial multiplexing systems. The new algorithms combine the recursive matrix inversion and ordered QR decomposition approaches, which are developed for nulling cancellation interaface Bell Labs layered space time (BLAST) and back substitution interface BLAST. As a result, new algorithms achieve total reduced complexities in frame based transmission with various payload lengths compared with the earlier methods. In addition, they enable shorter detection delay by carrying out a fast hybrid preprocessing. Moreover, the operation precision insensitivity of order optimization greatly relaxes the word length of matrix inversion, which is the most computational intensive part within the MIMO detection task.

In multiple antenna systems that use spatial multiplexing to raise transmission rates, it is preferable to use maximum likelihood (ML) detection to exploit the full receive diversity and minimize the error probability. In this paper, we present two tree based approximate ML detectors that use new two ordering criteria in conjunction with efficient search strategies. Unlike conventional tree detectors, the new detectors closely approximate the error performance of the exact ML detector while achieving a dramatic reduction in complexity. Moreover, they ensure a fixed detection delay and high level of parallelization in the tree search.

New volatile memory (e.g. Phase Change Memroy) presents fast access, large capacity, byte-addressable, and non-volatility features. These features will bring impacts on the design of current software system. It has become a hot research topic of how to manage it and provide what kind of interface for upper application to use it. This paper proposes FP-Heap. FP-Heap supports direct access to non-volatile memory through a persistent heap interface. With FP-Heap, traditional persistent object systems can benefit directly from the byte-persistency of non-volatile memory. FP-Heap extends current virtual memory manager (VMM) to manage non-volatile memory and maintain a persistent mapping relationship. Also, FP-Heap offers a lightweight transaction mechanism to support atomic update of persistent data, a simple namespace to facilitate data indexing, and a basic access control mechanism to support data sharing. Compared with previous work Mnemosyne, FP-Heap achieves higher performance by its customized VMM and optimized transaction mechanism.

The performance of conventional direction of arrival (DOA) methods is susceptible to the uncertainty of acoustic velocity in the underwater environment. To solve this problem, an underwater DOA estimation method with L-shaped array for wide-band signals under unknown acoustic velocity is proposed in this paper. The proposed method refers to the idea of incoherent signal subspace method and Root-MUSIC to obtain two sets of average roots corresponding to the subarray of the L-shaped array. And the geometric relationship between two vertical linear arrays is employed to derive the expression of DOA estimation with respect to the two average roots. The acoustic velocity variable in the DOA estimation expression can be eliminated in the proposed method. The simulation results demonstrate that the proposed method is more accurate and robust than other methods in an unknown acoustic velocity environment.

With the development of silicon-based Nano-photonics, Optical Network on Chip (ONoC) is, due to its high bandwidth and low latency, becoming an important choice for future multi-core networks. As a key ONoC technology, the arbitration scheme should provide differential arbitration service with high throughput and low latency for various types and priorities of traffic in CMPs. In this work, we propose a fast hierarchical arbitration scheme based on multi-level priority QoS. First, given multi-priority data buffer queue, arbiters provide differential transmissions with fair service for all nodes and guarantee the max-transmit-delay and min-communication-bandwidth for all queues. Second, arbiter adopts the transmit bound resource reservation scheme to reserve time slots for all nodes fairly, thereby achieving a throughput of 100%. Third, we propose fast arbitration with a layout of fast optical arbitration channels (FOACs) to reduce the arbitration period, thereby reducing packet transmitting delay. Simulation results show that with our hierarchical arbitration scheme, all nodes are allocated almost equal service access probability under various traffic patterns; thus, the min-communication-bandwidth and max-transmit-delay is guaranteed to be 5% and 80 cycles, respectively, under the overload demands. This scheme improves throughput by 17% compared to FeatherWeight under a self-similar traffic pattern and decreases arbitration delay by 15% compare to 2-pass arbitration, incurring a total power overhead of 5%.

This paper presents a two-dimensional (2D) DOA algorithm for double L-shaped arrays. The algorithm is applied to the underwater environment for eliminating the performance error caused by the sound speed uncertainty factor. By introducing the third dimensional array, the algorithm eliminates the sound velocity variable in the depression angle expression, so that the DOA estimation no longer considering the true value of unknown sound velocity. In order to determine the parameters of a three-dimensional array, a parameter matching method with the double L-shaped array is also proposed. Simulations show that the proposed algorithm outperforms the conventional 2D-DOA estimation algorithm in unknown sound velocity environment.

This paper proposes a simple and feasible decision-feedback channel tracking scheme for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems designed for wireless local area networks (LANs). In the proposed scheme, the channel state matrix for each subcarrier is tentatively estimated from a replica matrix of the transmitted signals. The estimated channel matrices, each derived at a different timing, are combined, and the previously estimated channel matrices are replaced with the latest ones. Unlike conventional channel tracking schemes based on a Kalman filter, the proposed scheme needs no statistical information about a MIMO channel, which makes the receiver structure quite simple. The packet error rate (PER) performances for the proposed scheme are evaluated on computer simulations. When there are three transmit and receive antennas, the subcarrier modulation scheme is 64 QAM, and the coding rate is 3/4, the proposed scheme keeps the SNR degradation at PER of 1e-2 less than 0.1 dB when the velocity of receiver is 3 km/h in an indoor office environment at 5 GHz band. In addition, compared to the conventional channel tracking scheme based on known pilot symbols, the proposed scheme improves throughput performance by 13.8% because it does not need pilot symbols. These results demonstrate that the proposed channel tracking scheme is simple and feasible for implementation in MIMO-OFDM systems based on wireless LANs.

In rich scattering environments, multiple antenna systems designed to accomplish spatial multiplexing have enormous potential of lifting the capacity of corresponding multiple input multiple output channels. In this paper, we present a new low complexity algorithm for decision feedback equalization detector in the SM scheme. The basic idea is to reduce the joint optimization problem to separate optimization problems to achieve better performance-complexity tradeoffs. Concretely, we separately optimize the detection order and the detector filters so that the complexity of the entire signal detection task is reduced. The new order search rule approximates the optimal Bell Labs layered space time (BLAST) approach from a geometrical perspective, and the detector filters are derived using a Cholesky based QR decomposition. The new algorithm is able to switch from zero forcing to minimum mean square error without additional operations and the computational effort is a small fraction of that in the optimal BLAST algorithm. Despite its low complexity, the error performance of new detector closely approximates that of the standard BLAST.

This letter proposes a blind phase compensation method for the phase errors in the Multi-Carrier Multiple-input multiple-output (MIMO) radar, which decouples the range and DOA coupling. The phase errors under the Linear Frequency Modulated Continuous Waveform (LFMCW) scheme are firstly derived, followed with the signal processing steps. Further, multiple targets with certain velocities can be handled uniformly without pre-knowledge of the actual range information of the targets. The evaluations of the DOA estimation performance are carried out through simulations, which validate the effectiveness of the proposed method.

To enhance the throughput while satisfying the quality of service (QoS) requirements of wireless local area networks (WLANs), this paper proposes a distributed coordination function-based (DCF-based) medium access control (MAC) protocol that realizes centralized radio resource management (RRM) for a basic service set. In the proposed protocol, an access point (AP) acts as a master to organize the associated stations and attempts to reserve the radio resource in a conventional DCF-manner. Once the radio resource is successfully reserved, the AP controls the access of each station by an orthogonal frequency division multiple access (OFDMA) scheme. Because the AP assigns radio resources to the stations through the opportunistic two-dimensional scheduling based on the QoS requirements and the channel condition of each station, the transmission opportunities can be granted to the appropriate stations. In order to reduce the signaling overhead caused by centralized RRM, the proposed protocol introduces a station-grouping scheme which groups the associated stations into clusters. Moreover, this paper proposes a heuristic resource allocation algorithm designed for the DCF-based MAC protocol. Numerical results confirm that the proposed protocol enhances the throughput of WLANs while satisfying the QoS requirements with high probability.

This paper presents a reduced-complexity maximum likelihood detection (MLD) scheme for orthogonal frequency division multiplexing with space division multiplexing (OFDM-SDM) systems. Original MLD is known to be an optimal scheme for detecting the spatially multiplexed signals. However, MLD suffers from an exponentially computational complexity because it involves an exhaustive search for the optimal result. In this paper, we propose a novel detection scheme, which drastically reduce the complexity of MLD while keeping performance losses small. The proposed scheme decouples the spatially multiplexed signals in two stages. In stage one, the estimated symbols obtained from zero-forcing (ZF) are used to limit the candidate symbol vectors. In stage two, to form a final estimate of the transmitted symbol vector, the Euclidean or original defined likelihood metric is examined over all symbol vectors obtained from stage 1. Both the bit error rate (BER) and packet error rate (PER) performances are evaluated over a temporally and spatially uncorrelated frequency selective channel through the computer simulations. For a four-transmit and four-receive OFDM-SDM system transmitting data at 144 Mbit/s and 216 Mbit/ss i.e., employing 16 Quadrature Amplitude Modulation (16QAM) and 64QAM subcarrier modulation over 16.6 MHz bandwidth channel, the degradation in required SNR from MLD for PER = 1% are about 0.6 dB and 1.5 dB, respectively. However, the complexity of MLD is reduced to 0.51000% and 0.01562%.

This paper describes the experimental evaluation of a testbed with a simple decision-feedback channel tracking scheme for MIMO-OFDM systems. The channel tracking scheme periodically estimates the channel state matrix for each subcarrier from received signals and replicas of the transmitted signal. The estimated channel state matrices, which are obtained at mutually different timings, are combined based on maximum ratio combining and used for MIMO signal detection. The testbed was implemented on field programmable gate arrays (FPGAs) of 1/5 scale, which confirms the implementation feasibility of the channel tracking scheme. The packet error rate (PER) and mobility performance of the testbed were measured. The testbed employed a 22 MIMO channel, zero-forcing algorithm for MIMO signal detection, 16QAM for the subcarrier modulation scheme, and coding rate of 1/2. The proposed scheme suppressed the increase in the required SNR for PER of 10-2 to less than 1 dB when the relative velocity between the transmitter and the receiver was less than 45 km/h assuming 5 GHz band operation. In addition, the proposed scheme offers 6.3% better throughput than the conventional scheme. The experimental results demonstrate that the channel tracking scheme implemented in the testbed effectively tracks the fluctuation of a MIMO channel.

Recent theoretical and experimental studies indicate that spatial multiplexing (SM) systems have enormous potential for increasing the capacity of corresponding multiple input multiple output (MIMO) channels in rich scattering environments. In this paper, we propose a new recursion based algorithm for Bell Labs layered space time (BLAST) signal detection in SM systems. The new algorithm uses an inflated recursion in the initialization and a deflated recursion in the iteration stage: as a result, the complexity is greatly reduced and the irregularity issues are completely avoided. Compared with the conventional fastest recursive approach, the complexity of our proposal is lower by a factor of 2 and it is also very implementation friendly.

To enhance the throughput of wireless local area networks (WLANs) by efficiently utilizing the radio resource, a distributed coordination function-based (DCF-based) orthogonal frequency division multiple access (OFDMA) WLAN system has been proposed. In the system, since each OFDMA sub-channel is assigned to the associated station with the highest channel gain, the transmission rate of DATA frames can be enhanced thanks to multi-user diversity. However, the optimum allocation of OFDMA sub-channels requires the estimation of channel state information (CSI) of all associated stations, and this incurs excessive signaling overhead. As the number of associated stations increases, the signaling overhead severely degrades the throughput of DCF-based OFDMA WLAN. To reduce the signaling overhead while obtaining a sufficient diversity gain, this paper proposes a channel access scheme that performs multiple DCF-based channel access. The key idea of the proposed scheme is to introduce additional DCF-based prioritized access along with the traditional DCF-based random access. In the additional DCF-based prioritized access, by dynamically adjusting contention window size according to the CSI of each station, only the stations with better channel state inform their CSI to the access point (AP), and the signaling overhead can be reduced while maintaining high multi-user diversity gain. Numerical results confirm that the proposed channel access scheme enhances the throughput of OFDMA WLAN.